Multi-objective path planning for unmanned surface vehicle with currents effects

被引：179

作者：

Ma, Yong ^{[1
,2
]}

Hu, Mengqi ^{[3
]}

Yan, Xinping ^{[4
]}

机构：

[1] Wuhan Univ Technol, Sch Nav, 1178 Heping Rd, Wuhan 430063, Hubei, Peoples R China

[2] Hubei Key Lab Inland Shipping Technol, 1178 Heping Rd, Wuhan 430063, Hubei, Peoples R China

[3] Univ Illinois, Dept Mech & Ind Engn, Chicago, IL 60607 USA

[4] Wuhan Univ Technol, Natl Engn Res Ctr Water Transport Safety, 1178 Heping Rd, Wuhan 430063, Hubei, Peoples R China

来源：

ISA TRANSACTIONS | 2018年 / 75卷

基金：

中国博士后科学基金; 美国国家科学基金会;

关键词：

Unmanned surface vehicle; Multi-objective path planning; Currents; Dynamic augmented multi-objective particle; swarm optimization; AUTONOMOUS UNDERWATER VEHICLES; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; NAVIGATION; SHIP; STRATEGIES; COLREGS; MODEL;

D O I：

10.1016/j.isatra.2018.02.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper investigates the path planning problem for unmanned surface vehicle (USV), wherein the goal is to find the shortest, smoothest, most economical and safest path in the presence of obstacles and currents, which is subject to the collision avoidance, motion boundaries and velocity constraints. We formulate this problem as a multi-objective nonlinear optimization problem with generous constraints. Then, we propose the dynamic augmented multi-objective particle swarm optimization algorithm to achieve the solution. With our approach, USV can select the ideal path from the Pareto optimal paths set. Numerical simulations verify the effectiveness of our formulated model and proposed algorithm. (C) 2018 ISA. Published by Elsevier Ltd. All rights reserved.

引用

页码：137 / 156

页数：20

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